As generative AI intensifies workloads and blurs the boundaries between work and non-work, organizations should look to implement sustainable AI practices. While these steps may help get the most out of gen AI, 2026 looks to be the year where predictive AI use cases take over.
The trend: Generative AI is making it easier to do more work, but harder to stop.
The details: Ongoing research by Harvard Business Review finds that over an 8 month period, employees using generative AI worked at a faster pace, took on a broader scope of tasks, and extended work into more hours of the day, often without being asked to do so.
Why it matters: Higher short-term productivity risks fatigue, burnout and increased errors. Organizations should look to implement AI working practices like intentional pauses and human grounding to establish a sustainable working culture.
The trend: While generative AI grabs the headlines, predictive AI is driving more business impact behind the scenes.
The details: In Forbes, Eric Siegel argues that predictive AI (models that forecast outcomes like churn risk, demand, and inventory management), consistently delivers higher returns, can operate autonomously and is generally cheaper than generative AI.
Why it matters: As enterprises are struggling to deliver tangible ROI on AI projects, predictive AI projects, as well as a hybridization of the two approaches, may deliver the greatest value.
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Phase 1 is launching in Q1, with later phases bringing features like pipeline creating and analytics context coming soon!
Anthropic has raised $30 billion in their latest (series G) funding round, bringing their valuation to $380 billion. Anthropic's revenue has grown 10x in each of the past 3 years, driven by increasing enterprise adoption and agentic coding tools. In 2026, over 500 customers are spending over $1 million a year on Claude, and 8 of the Fortune 10 are cloud customers.
Audience Insights 🔮
How does your team use AI today?
Last time we asked how teams are actually using AI on a day-to-day basis.
Chat & Q&A was the #1 use case
Workflow automation and research & analysis shared 2nd place, with 33.3% of teams listing one of the two as their main AI tool use
Content and image generation came in 3rd place, showing that teams are still hesitant to use predictive AI, at least in their daily workflows
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